Phương pháp nghiên cứu khoa học: interpretive research methods in computer science

Interpretive research methods in computer science
Kirsti E. Berntsen, Jennifer Sampson and Thomas Østerlie
Norwegian University of Science and Technology,
Trondheim, Norway.
“[A]ll researchers interpret the world through some sort of conceptual lens
formed by their beliefs, previous experiences, existing knowledge, assumptions
about the world and theories about knowledge and how it is accrued. The
researcher’s conceptual lens acts as a filter: the importance placed on the
huge range of observations made in the field (choosing to record or note some
observations and not others, for example) is partly determined by this filter”
(Carroll and Swatman, 2000, pp.118-119).

Introduction
Research is interpretive if it is assumed that our knowledge of reality is gained only
through social constructions such as language, consciousness, shared meanings,
documents and other artefacts. In information systems interpretive research is “aimed at
producing an understanding of the context of the information system and the process
whereby the information system influences and is influenced by its context” (Walsham,
1993). Interpretive research often involves using qualitative methods from which to
understand the data collected and analysed during the research process. Nevertheless
research is not necessarily interpretive just because the type of data collected is
qualitative. Moreover there are ways of using numerical data in interpretive research, as
there are ways within traditional research of using non-quantitative data. The most
important distinction between traditional research approaches and interpretive research
are the underlying philosophical assumptions. A key task in interpretive research is
seeking meaning in context - the subject matter must be set in its social and historical
context so the reader can see how the current situation emerged (Klein and Myers, 1999).
In addition because interpretive research is undertaken with different assumptions about
knowledge and being it is necessary for the researcher to make clear the ontological and
epistemological underpinnings of the research.

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Experimental software engineering
Experimental software engineering1 ( Wohlin et al. 2000) is a sub-field of software
engineering. ESE aims at applying empirical theories and methods for understanding and
improving the software development process in organizations. ESE is a multi-disciplinary
field, building upon subsidiary fields such as statistics, sociology, psychology, and
computer science. The main objective of ESE is to evaluate tools, techniques, and
technologies used in software engineering empirically, and thereby enhancing the state of
the art and practice in software engineering. The method employed to achieve the goal is
to run empirical investigations with the software development process as the object of
study.
Wohlin et al. (2000) provides a five step research method for doing software engineering
experiments:
1. Experiment definition. In this step the hypothesis is defined, along with the
objectives and goals of the experiment. The hypothesis, at this stage, need not be
formally stated, but should be stated clearly. The objective and goals are found by
asking the following questions: what is studied? (object of study), what is the
purpose of the experiment? which effect is studied? (quality focus) whose view is
assumed? (perspective of the study) and where is the study conducted? (context).
2. Experiment planning. At this stage, the hypothesis is formalized including a null
hypothesis. Input/independent variables and output/dependent variables are

determined. A suitable experiment design is chosen, and the potential validity
problems with the results are discussed.
3. Experiment operation. Subjects and the materials needed (for data collection
forms) for the experiment is prepared, before executing the experiment. The
primary objective of this stage is to gather data for the next step.
4. Analysis and interpretation. Descriptive statistics are used to understand the data
gathered during step three. A possible reduction of the data set must be

1

Abbreviated to ESE hereafter.

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considered. After the data has been reduced, a hypothesis test is performed using
statistical techniques.
5. Presentation and package. This stage is concerned with presenting and packaging
the findings. It is important that the experiment design is clear, to allow for
replication as this is an important mechanism for validating the findings.
Experimental software engineering is based on a hypothetic-deductive research model.
The primary problem facing any empirical researcher is the wealth and complexity of the
real world. The hypothetic-deductive research model ‘solves’ this by reducing the scope

of the empirical enquiry. The controlled experiment is a good example of such a
reduction, where the empirical world is reduced to a set of independent and dependent
variables, subjects, and the treatments applied to the subjects. The ontology of this
research philosophy is that the real world can be divided into small bits that can later be
reassembled into a complete picture.

Towards interpretive software engineering
Recent studies (Conradi and Fugetta 2003, Dybå 2001) warrant the need for increased
awareness in ESE research. This has implications on the data material available. Tools,
techniques, and methods provide us with quantitative data that we may analyse
statistically. Empirical software engineering’s current focus on hypothetic-deductive
research reinforces the disciplines focus on quantifiable objects of study. However, doing
investigations including the organizational dimension, we are faced with a whole array of
other data sources to analyse: meeting minutes, internal memos, e-mails, contracts,
handbooks of all sorts, staged scenarios (i.e. usability testing) and ethnographic
experience renditions (i.e. anthropology-like observations), just to mention a few. A
common denominator of these data sources is that they are all documented in a nonnumerical fashion, textually or by visio/audio recordings, (which are often reduced to
text), and therefore qualitative. In other words, empirical investigations that include the
organizational and social dimensions require methods for doing textual analysis to enrich
the research within the field.

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While there exists qualitative research within ESE (Seaman 1999, Dingsøyr 2002), most
published empirical software engineering research is hypothetic-deductive. An approach
to empirical research based on textual data is interpretive research. This approach is
currently being used within parts of the information systems community (Walsham 1992,
Myers 1992, Ciborra 2004). The title interpretive should not be understood as exclusive,
in that there is no interpretation in other methods for investigations. Interpretative, in this
case, means that the entire research effort focuses on the researcher continuously
interpreting data, sources, and results produced by different methods for gathering data
and analysis of these.

Case study research
Taking an interpretivist philosphical stance Walsham (1993) would claim that, “the most
appropriate method for conducting empirical research in the interpretive tradition is the
in-depth case study” (p.14). Case study research can be classified as a qualitative
method, and, the purpose of which is to try to understand, or interpret, phenomena in
terms of the subjective meanings people bring to them (Denzin, 1994). Klein and Myers
(1999) point out “positive criteria...are inappropriate for interpretive research” (p.68).
The work of Yin (1994) on Case Study Research Design is recognised and cited by many
IS researchers as providing an important contribution to case study design. According to
Yin (1994), a case study is defined as “an empirical inquiry that investigates a
contemporary phenomenon within its real-life context, especially when the boundaries
between phenomenon and context are not clearly evident” (ibid. p.13). However, the
nearest the author comes to addressing the challenge of ‘quality’ in case study design is
through the use of a case study protocol. He quite correctly deduces that: “A case study
protocol is more than an instrument. The protocol contains the instrument but also
contains the procedures and the general rules that should be followed in using the
instrument.” (ibid. p.63). He maintains that the protocol should have the following
sections: an overview of the case study project, field procedures, case study questions,
and a guide for the case study report. All of these are important but the problem is that it

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often difficult to accurately document this level of detail at the beginning of the research
project.
Like Yin (1994), the research of Walsham (1995) is recognised and cited by many as
providing an important contribution to the nature and method for interpretive case
studies. He also recognised the lack of “a synthesised view of the nature and conduct of
case studies with specific reference to the field of computer-based IS” (ibid. p.74).
Walsham (1995) discusses: the research tradition of interpretive research, the use of
theory in interpretive studies, four types of generalisations (extending Yin’s work), and
conduct of empirical work.

Principles and quality guidelines for interpretive research
Interpretive field research includes in-depth case studies and ethnographies. Klein and
Myers (1999) comment that as “the interest in interpretative research has
increased...researchers, reviewers and editors have raised questions about how
interpretive field reasearch should be conducted and how its quality can be assessed”
(p.67). They have devised a set of principles for conducting and evaluating interpretive
field studies in IS (Klein and Myers, 1999). The principles they propose are fundamental
ideas derived from philosophical writings that mostly to the conduct and evaluation of
interpretive research in the hermeneutic nature. Most importantly, they conclude that,

“while not all of the principles may apply in every situation, their systematic
consideration is likely to improve the quality of future interpretive field
research in information systems (especially that of a hermeneutic nature)”
(ibid. p.70).
The protocol steps described by Yin (1994) would be of particular use for IS case study
research if they were components of a more detailed set of practical guidelines. Atkins
and Sampson (2002) have provided more practical critical appraisal guidelines for
conducting single case study research in the interpretive tradition. The purpose of which
is to provide a means to validate both academic and practitioner sourced literature,
through the use of hierarchies of evidence.

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Social theories for understanding IT in an organisation
So far we have discussed the motivation for using interpretive methods for enhancing
ESE research and described interpretive case studies. Depending on the research focus,
interpretation can be aided by choosing one or several social theories in order to
understand the relationships between work, people and technology. In addition, the use of
technology as an aspect in such theory is important for the subject of study. In the
following sections we will describe two social theories2 for interpretation, namely Actor
Network Theory and Activity Theory.

Activity theory (AT)
Kutti (1991) states that there has always been a dichotomy in the behavioural and the
social sciences between the individual and the social. A solution to this is an intermediary
concept which is the activity, which incorporates both the individual human agency as
well as the social context. An activity is seen as a minimal meaningful context for
individual actions and a suitable basic unit for analysis. An activity is better defined than
an arbitrary context, but also more manageable than a whole social system. AT is a
philosophical framework for studying different forms of human praxis as processes of
development, where both the individual and the social levels are interlinked (Kutti, 1991)
It draws on German philosophy (Kant and Hegel), the writings of Marx and Engels on the
concept of work as well as the Soviet cultural-historical school of psychology founded by
Vygotski (1978), Leontjev (1978, 1981) and Lurija.
The main concepts for activity theory are the following:
1.

2

Activity: a fundamental type of context (meaningless to study smaller objects of
research for essentially human qualities without loosing the essence of the
phenomenon in the basic context.

Bratteteig and Gregory (1999) describe other social theories such as

Structuration Theory ( Orlikowsky),

Interaction Theory (Grounded Theory) as well as Speech Act Theory (Suchman).

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2.
3.
4.
5.
6.
7.
8.
9.
10.
11.
12.
13.

An activity has an active subject (individual or collective) who understands the
motive of the activity – the object. There may be non-active participants in the
activity – i.e. they do not know the motive/object (“the boss knows”).
The transformation of the object towards some desired state is what motivates the
existence of an activity.
An activity exists in a material environment and transforms it. (the term material
comes from Marxist philosophy and signifies not only “touchable” things but
everything conscious which exists outside the individual.
An activity is a historically developing phenomenon.
An activity is a collective phenomenon.

Individuals can participate in several activities - basic units of development and
human life.
When crossing organizational or other conceived borders of an activity, only
inclusion of active subjects sharing an object is relevant.
Activities temporarily merge. Actions are usually polymotivated, that is they are
simultaneously part of separate “overlapping” activities.
Contradictions are the force behind the development of an activity
Primary contradictions between the objects or outcomes of two separate activities
may introduce secondary contradictions into the activities.(Engestrøm 2000)
An activity is realized through the conscious and purposeful actions by participants.
Relationships within an activity are culturally mediated.

Engestrøms (1987) structural model of activity is shown below. The binary relationship
between subject and object of activity is replaced with a mediated relationship through a
“tool or instrument” which is history etc. Also there is a relationship between the subject
and the community (who share the same object) which is also mediated by rules. Finally
the relationship between community and object is mediated by “division of labour”. The
mediating members are continuously being reconstructed during the existence of the
activity - the activity results in an outcome.

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tool

subject

object

rules

community

outcome

Division of
labour

Fig. 1 Basic structure of an activity
AT identifies a three-level hierarchy of collaborative activity (Engestrøm et.al. 1997): the
co-ordinated, the co-operative and co-construction. There are dynamic transformations
between the levels of collaborative activities, shown at Figure 2 below.
Co-construction
Reflection on the
Object of work

↑

↓

Implementation:
Stabilizing the Object of work

Co-operation
Reflection on the
Means of work

↑

↓

Routinization: Stabilizing the
Means of work

Co-ordination

Fig.2. The dynamics of cooperative work

Actor network theory (ANT)
Actor network theory is based on the works of Callon (1986, 1991) and Latour (1987).
“Actor Network Theory views society as a completely interwoven socio-technical web”

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(Hanseth and Monteiro, 1997, p. 2). The theory has ties to semiotics which is the study of

order-building (Akrich and Latour, 1992, p.259) and includes both human and nonhuman entities in addition to signs. In attributing symmetry to all these entities,
technology, amongst others, gets promoted to the status of actor. This allows a more
detailed look at technology and the role it plays through the hands of the social entities
that make it, appropriate it and inscribe motivations and abilities into it, or with it. This
contrasts with the other social theories mentioned previously, which all view technology
as having enabling or restricting qualities but still see it as secondary to the main focus of
the theories. It is important to remember that this promotion of technology’s status in
ANT is in fact the act of the social actors and is an inherent part of modern organization
of society as such. The social actors use technology to their own or others end, be it
conscious or not, depending on how the actor network gets aligned.
The basic concepts are described by Callon (1986):
1. Actor: any element which bends space around itself in trying to make other
elements adopt it’s will and become dependent upon it. Actors can be: indivuals,
technology, standards, organizations etc.
2. Actor Network: a heterogeneous network of

aligned interests , or

alignments/translations are underway
3. Translation: the process of creating an aligned network. It is helpful to focus on
separate actors and separate translations in different parts of the network.
4. Inscription: A process of creating technical artefacts that would ensure
the protection of an actor's interests.
5. Irreversibility: The degree to which it is subsequently impossible to return
to a point where alternative possibilities exist.
6. Black box: an immutable inscription/translation has occurred and a part of the
network which is stabilised can be collapsed into a Black box which does not
need to be delved into. The Black box can be viewed as a sum of the original
actors that are black-boxed into it. Irreversibility has occurred.
Central to ANT is the enrolment of actors to courses of action that come about by

introducing technical actors into the network which then influence the alignment of
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interests in the network. Inscriptions can be weak or strong – and may differ in regards to
different actors. Strong inscriptions result in irreversibility. In picturing the groupware
tool as an actor/actant one may attribute humanlike abilities, limitations and intentions to
the technology. This can be a fruitful approach and analogy of technology as it allows us
to endow the technology with various degrees of different qualities – much like each of
us do with different people. The affordance of the technology-actant will be relative to
and determined, by each separate actor’s understanding of the other actors/actants. ANT
allows us in other words to take social construction seriously in our understanding of the
role of technology, without giving us detailed guidelines as to what aspects of technology
should or could be considered. Our experience with humans should provide us with an
ample vocabulary to understanding and describing the actant both in regard to inscribed
motives and functionality. Only real world-situations can define the role of technology
for various people in various settings – and people can redefine these roles by new
inscriptions and translations.
Overall ANT focuses on the processes which result in change and the role of the artefacts
as well as humans within these processes. The processes are viewed as networks of
action. ANT can be used to attempt to lift focus from the local engineering aspects of
making things work to the fact that human motivations and politics, as well as
organizational settings are an equally important aspect of technological success.

Conclusion
Our claim is that interpretive research can help computer scientists to understand human
thought and action in social and organizational contexts; it has the potential to produce
deep insights into computer science including the management of information systems,
information systems development and software engineering.
We have briefly discussed case study research as a qualitative method, where the purpose
of which is to try to understand, or interpret, phenomena in terms of the subjective
meanings people bring to them (Denzin, 1994). In addition we have described two social
theories for interpretation; Actor Network Theory (ANT) and Activity Theory (AT). The
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strength of ANT is the simplicity of concepts and the explicit description of technology
as a carrier of inscriptions that influence our actions and choices. AT looks more closely
at work and interaction in particular. AT also gives status to technology and artefacts in
putting them on the same level as rules, laws and division of labour.

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